Overview

Dataset statistics

Number of variables20
Number of observations351
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory55.0 KiB
Average record size in memory160.4 B

Variable types

NUM17
BOOL3

Reproduction

Analysis started2020-08-25 01:26:02.917478
Analysis finished2020-08-25 01:26:50.632364
Duration47.71 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

1 has constant value "0" Constant
Dataset has 1 (0.3%) duplicate rows Duplicates
15 has 45 (12.8%) zeros Zeros
19 has 34 (9.7%) zeros Zeros
27 has 4 (1.1%) zeros Zeros
8 has 32 (9.1%) zeros Zeros
24 has 24 (6.8%) zeros Zeros
21 has 37 (10.5%) zeros Zeros
12 has 31 (8.8%) zeros Zeros
32 has 48 (13.7%) zeros Zeros
9 has 39 (11.1%) zeros Zeros
4 has 38 (10.8%) zeros Zeros
16 has 25 (7.1%) zeros Zeros
17 has 30 (8.5%) zeros Zeros
5 has 46 (13.1%) zeros Zeros
13 has 37 (10.5%) zeros Zeros
11 has 37 (10.5%) zeros Zeros
2 has 25 (7.1%) zeros Zeros

Variables

15
Real number (ℝ)

ZEROS

Distinct count270
Unique (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07113233618233618
Minimum-1.0
Maximum1.0
Zeros45
Zeros (%)12.8%
Memory size2.9 KiB
2020-08-25T01:26:50.676532image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.081705
median0
Q30.308975
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.39068

Descriptive statistics

Standard deviation0.4583706723
Coefficient of variation (CV)6.443914215
Kurtosis0.5508428289
Mean0.07113233618
Median Absolute Deviation (MAD)0.15727
Skewness-0.09810551086
Sum24.96745
Variance0.2101036732
2020-08-25T01:26:50.781260image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
04512.8%
 
-1205.7%
 
1195.4%
 
-0.0194210.3%
 
0.2732210.3%
 
0.0115110.3%
 
0.4174310.3%
 
0.1463810.3%
 
0.0185810.3%
 
-0.0335210.3%
 
0.0702710.3%
 
0.483610.3%
 
0.77510.3%
 
0.0336610.3%
 
-0.5901710.3%
 
0.9368210.3%
 
0.0029910.3%
 
0.273810.3%
 
0.7952310.3%
 
-0.0791710.3%
 
0.3143910.3%
 
0.3877810.3%
 
0.4147110.3%
 
0.1019510.3%
 
0.0505810.3%
 
Other values (245)24569.8%
 
ValueCountFrequency (%) 
-1205.7%
 
-0.9751510.3%
 
-0.8351910.3%
 
-0.6806510.3%
 
-0.6770810.3%
 
-0.6366810.3%
 
-0.6143610.3%
 
-0.5901710.3%
 
-0.5889910.3%
 
-0.5753510.3%
 
ValueCountFrequency (%) 
1195.4%
 
0.9368210.3%
 
0.9140410.3%
 
0.9066510.3%
 
0.8927410.3%
 
0.8844410.3%
 
0.8628410.3%
 
0.8503810.3%
 
0.8480410.3%
 
0.842910.3%
 

19
Real number (ℝ)

ZEROS

Distinct count266
Unique (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.024024700854700848
Minimum-1.0
Maximum1.0
Zeros34
Zeros (%)9.7%
Memory size2.9 KiB
2020-08-25T01:26:50.901067image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.23467
median0
Q30.13437
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.36904

Descriptive statistics

Standard deviation0.5190760918
Coefficient of variation (CV)-21.60593362
Kurtosis-0.1031621599
Mean-0.02402470085
Median Absolute Deviation (MAD)0.19444
Skewness0.05960111262
Sum-8.43267
Variance0.2694399891
2020-08-25T01:26:51.006655image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0349.7%
 
-1288.0%
 
1246.8%
 
0.1272720.6%
 
0.120.6%
 
0.0361710.3%
 
-0.3219210.3%
 
-0.0099110.3%
 
0.5510210.3%
 
0.265910.3%
 
-0.1365210.3%
 
0.0356610.3%
 
-0.0126610.3%
 
0.7803610.3%
 
0.0527910.3%
 
-0.8895210.3%
 
0.0140810.3%
 
0.6574710.3%
 
-0.3296310.3%
 
0.530710.3%
 
0.0138610.3%
 
0.0661810.3%
 
-0.7364110.3%
 
0.7555410.3%
 
0.0526310.3%
 
Other values (241)24168.7%
 
ValueCountFrequency (%) 
-1288.0%
 
-0.9359910.3%
 
-0.8895210.3%
 
-0.8778710.3%
 
-0.8627510.3%
 
-0.8606310.3%
 
-0.8600210.3%
 
-0.8565410.3%
 
-0.8558310.3%
 
-0.8484810.3%
 
ValueCountFrequency (%) 
1246.8%
 
0.9509910.3%
 
0.9310910.3%
 
0.9294910.3%
 
0.8595210.3%
 
0.8492210.3%
 
0.7977710.3%
 
0.7974910.3%
 
0.7961710.3%
 
0.7952510.3%
 

27
Real number (ℝ)

ZEROS

Distinct count281
Unique (%)80.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.06953760683760683
Minimum-1.0
Maximum1.0
Zeros4
Zeros (%)1.1%
Memory size2.9 KiB
2020-08-25T01:26:51.124417image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.443165
median-0.01769
Q30.153535
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.5967

Descriptive statistics

Standard deviation0.5500252428
Coefficient of variation (CV)-7.909752259
Kurtosis-0.3431892824
Mean-0.06953760684
Median Absolute Deviation (MAD)0.23985
Skewness0.0667074171
Sum-24.4077
Variance0.3025277677
2020-08-25T01:26:51.232310image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-14011.4%
 
1298.3%
 
041.1%
 
-0.0083810.3%
 
-0.1683710.3%
 
0.0550310.3%
 
-0.8137210.3%
 
-0.0482210.3%
 
-0.7150410.3%
 
-0.5320610.3%
 
-0.0176910.3%
 
-0.0012810.3%
 
0.0109610.3%
 
0.1328210.3%
 
-0.6195910.3%
 
0.0222610.3%
 
0.2022510.3%
 
-0.0135810.3%
 
0.6633510.3%
 
-0.2386410.3%
 
0.0201910.3%
 
-0.1089710.3%
 
0.6912910.3%
 
-0.7666710.3%
 
0.0816510.3%
 
Other values (256)25672.9%
 
ValueCountFrequency (%) 
-14011.4%
 
-0.9393910.3%
 
-0.9329610.3%
 
-0.9122110.3%
 
-0.8658310.3%
 
-0.86510.3%
 
-0.8612210.3%
 
-0.8566910.3%
 
-0.8513710.3%
 
-0.825110.3%
 
ValueCountFrequency (%) 
1298.3%
 
0.8824810.3%
 
0.8379610.3%
 
0.7854110.3%
 
0.7800410.3%
 
0.7510.3%
 
0.7388510.3%
 
0.7238610.3%
 
0.7161310.3%
 
0.7137410.3%
 

26
Real number (ℝ)

Distinct count256
Unique (%)72.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5416407977207977
Minimum-1.0
Maximum1.0
Zeros0
Zeros (%)0.0%
Memory size2.9 KiB
2020-08-25T01:26:51.354892image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.64201
Q10.286435
median0.70824
Q30.999945
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.71351

Descriptive statistics

Standard deviation0.5162046654
Coefficient of variation (CV)0.9530387437
Kurtosis1.021871153
Mean0.5416407977
Median Absolute Deviation (MAD)0.29176
Skewness-1.287052977
Sum190.11592
Variance0.2664672566
2020-08-25T01:26:51.470541image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
18825.1%
 
-192.6%
 
0.7082410.3%
 
0.6184710.3%
 
-0.2283910.3%
 
-1e-0510.3%
 
0.2575810.3%
 
0.6865610.3%
 
0.1681310.3%
 
0.2920810.3%
 
0.6753810.3%
 
0.7671710.3%
 
-0.199410.3%
 
-0.1914910.3%
 
-0.6323710.3%
 
0.5757710.3%
 
-0.1655610.3%
 
0.4651410.3%
 
0.5680410.3%
 
0.8379610.3%
 
0.6541910.3%
 
-0.7035210.3%
 
0.9214810.3%
 
-0.015310.3%
 
0.3975210.3%
 
Other values (231)23165.8%
 
ValueCountFrequency (%) 
-192.6%
 
-0.8331410.3%
 
-0.7709710.3%
 
-0.7184410.3%
 
-0.7173110.3%
 
-0.7035210.3%
 
-0.6792510.3%
 
-0.6755710.3%
 
-0.6665110.3%
 
-0.6516510.3%
 
ValueCountFrequency (%) 
18825.1%
 
0.9998910.3%
 
0.9984210.3%
 
0.9918810.3%
 
0.988210.3%
 
0.9855610.3%
 
0.9803310.3%
 
0.975410.3%
 
0.9697410.3%
 
0.9670910.3%
 

8
Real number (ℝ)

ZEROS

Distinct count244
Unique (%)69.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5118480911680912
Minimum-1.0
Maximum1.0
Zeros32
Zeros (%)9.1%
Memory size2.9 KiB
2020-08-25T01:26:51.592391image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.355485
Q10.08711
median0.68421
Q30.95324
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.86613

Descriptive statistics

Standard deviation0.5070655269
Coefficient of variation (CV)0.9906562818
Kurtosis0.6873606011
Mean0.5118480912
Median Absolute Deviation (MAD)0.31579
Skewness-1.091865491
Sum179.65868
Variance0.2571154485
2020-08-25T01:26:51.698834image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
16418.2%
 
0329.1%
 
-1113.1%
 
0.6363620.6%
 
-0.3333320.6%
 
0.820.6%
 
0.5571710.3%
 
0.238110.3%
 
-0.4262510.3%
 
0.693210.3%
 
-0.0364310.3%
 
0.9276510.3%
 
0.7427310.3%
 
0.7115710.3%
 
-0.3776410.3%
 
-0.8510.3%
 
0.910.3%
 
0.9860210.3%
 
0.9587810.3%
 
-0.269710.3%
 
0.0740510.3%
 
0.3050810.3%
 
0.7367310.3%
 
0.0877610.3%
 
0.717610.3%
 
Other values (219)21962.4%
 
ValueCountFrequency (%) 
-1113.1%
 
-0.8709710.3%
 
-0.8510.3%
 
-0.5594110.3%
 
-0.490210.3%
 
-0.4262510.3%
 
-0.3803310.3%
 
-0.3776410.3%
 
-0.3333320.6%
 
-0.3322110.3%
 
ValueCountFrequency (%) 
16418.2%
 
0.9983810.3%
 
0.9970910.3%
 
0.9944810.3%
 
0.9937410.3%
 
0.992910.3%
 
0.9906110.3%
 
0.987210.3%
 
0.986310.3%
 
0.9860210.3%
 

24
Real number (ℝ)

ZEROS

Distinct count256
Unique (%)72.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.39613467236467237
Minimum-1.0
Maximum1.0
Zeros24
Zeros (%)6.8%
Memory size2.9 KiB
2020-08-25T01:26:51.815454image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.87839
Q10
median0.55389
Q30.90524
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.90524

Descriptive statistics

Standard deviation0.5784508875
Coefficient of variation (CV)1.460237964
Kurtosis-0.1370876483
Mean0.3961346724
Median Absolute Deviation (MAD)0.41963
Skewness-0.8815884425
Sum139.04327
Variance0.3346054293
2020-08-25T01:26:51.923211image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
15716.2%
 
0246.8%
 
-1154.3%
 
0.6666720.6%
 
0.520.6%
 
0.8723410.3%
 
0.6707710.3%
 
0.6927410.3%
 
0.7733610.3%
 
0.8492610.3%
 
0.4852610.3%
 
0.8454710.3%
 
0.9204910.3%
 
0.8848710.3%
 
-0.0411910.3%
 
-0.0874810.3%
 
0.7341310.3%
 
0.4792910.3%
 
0.8510610.3%
 
0.7713810.3%
 
0.537510.3%
 
0.7061910.3%
 
0.0083810.3%
 
0.5681110.3%
 
-0.0286210.3%
 
Other values (231)23165.8%
 
ValueCountFrequency (%) 
-1154.3%
 
-0.9898810.3%
 
-0.9157410.3%
 
-0.9030210.3%
 
-0.8537610.3%
 
-0.8479210.3%
 
-0.8319210.3%
 
-0.7833410.3%
 
-0.7527310.3%
 
-0.7426510.3%
 
ValueCountFrequency (%) 
15716.2%
 
0.9989910.3%
 
0.9969510.3%
 
0.9897110.3%
 
0.987510.3%
 
0.9840110.3%
 
0.9816410.3%
 
0.9783810.3%
 
0.9735210.3%
 
0.9712710.3%
 

21
Real number (ℝ)

ZEROS

Distinct count265
Unique (%)75.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.008295897435897433
Minimum-1.0
Maximum1.0
Zeros37
Zeros (%)10.5%
Memory size2.9 KiB
2020-08-25T01:26:52.044328image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.24387
median0
Q30.18876
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.43263

Descriptive statistics

Standard deviation0.5181658868
Coefficient of variation (CV)62.4604982
Kurtosis-0.128649046
Mean0.008295897436
Median Absolute Deviation (MAD)0.21326
Skewness0.06680524004
Sum2.91186
Variance0.2684958863
2020-08-25T01:26:52.149675image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
03710.5%
 
1308.5%
 
-1216.0%
 
0.0007520.6%
 
-0.0333310.3%
 
-0.0803910.3%
 
-0.5560510.3%
 
-0.7631610.3%
 
-0.0497110.3%
 
-0.1195310.3%
 
-0.310.3%
 
0.508110.3%
 
-0.8221710.3%
 
-0.0037710.3%
 
-0.6627810.3%
 
0.1425810.3%
 
-0.0029910.3%
 
-0.1152610.3%
 
-0.0189110.3%
 
0.1415710.3%
 
-0.0337710.3%
 
-0.2377410.3%
 
0.1219510.3%
 
0.3050810.3%
 
0.0767710.3%
 
Other values (240)24068.4%
 
ValueCountFrequency (%) 
-1216.0%
 
-0.9359610.3%
 
-0.9253610.3%
 
-0.8999110.3%
 
-0.8906410.3%
 
-0.8899910.3%
 
-0.8649810.3%
 
-0.8559710.3%
 
-0.8520510.3%
 
-0.8300710.3%
 
ValueCountFrequency (%) 
1308.5%
 
0.927310.3%
 
0.9200110.3%
 
0.8938310.3%
 
0.8561510.3%
 
0.8526810.3%
 
0.8216210.3%
 
0.8075410.3%
 
0.7696910.3%
 
0.7619310.3%
 

12
Real number (ℝ)

ZEROS

Distinct count238
Unique (%)67.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.40080119658119656
Minimum-1.0
Maximum1.0
Zeros31
Zeros (%)8.8%
Memory size2.9 KiB
2020-08-25T01:26:52.268061image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.93487
Q10
median0.64407
Q30.955505
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.955505

Descriptive statistics

Standard deviation0.622186124
Coefficient of variation (CV)1.552355954
Kurtosis-0.4039937329
Mean0.4008011966
Median Absolute Deviation (MAD)0.35593
Skewness-0.8762252925
Sum140.68122
Variance0.387115573
2020-08-25T01:26:52.375664image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
16518.5%
 
0318.8%
 
-1174.8%
 
0.4736820.6%
 
0.1666720.6%
 
0.6209920.6%
 
0.8526910.3%
 
0.7793710.3%
 
0.5975310.3%
 
0.092510.3%
 
-0.6135210.3%
 
-0.0373610.3%
 
0.690510.3%
 
-0.7605110.3%
 
-0.0315810.3%
 
0.7168510.3%
 
0.7622110.3%
 
0.2893110.3%
 
0.9788810.3%
 
0.4467510.3%
 
0.1276610.3%
 
0.672610.3%
 
0.6472510.3%
 
0.9967610.3%
 
0.9582410.3%
 
Other values (213)21360.7%
 
ValueCountFrequency (%) 
-1174.8%
 
-0.9388210.3%
 
-0.9309210.3%
 
-0.9209910.3%
 
-0.8719210.3%
 
-0.8662210.3%
 
-0.8644310.3%
 
-0.8421110.3%
 
-0.8185710.3%
 
-0.8169910.3%
 
ValueCountFrequency (%) 
16518.5%
 
0.9974510.3%
 
0.9967610.3%
 
0.9917310.3%
 
0.9891910.3%
 
0.98510.3%
 
0.9834310.3%
 
0.981210.3%
 
0.979810.3%
 
0.9792110.3%
 

32
Real number (ℝ)

ZEROS

Distinct count245
Unique (%)69.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.34936364672364667
Minimum-1.0
Maximum1.0
Zeros48
Zeros (%)13.7%
Memory size2.9 KiB
2020-08-25T01:26:52.668230image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.65533
Q10
median0.40956
Q30.813765
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.813765

Descriptive statistics

Standard deviation0.5226633728
Coefficient of variation (CV)1.496043958
Kurtosis-0.1689502847
Mean0.3493636467
Median Absolute Deviation (MAD)0.40956
Skewness-0.6060703823
Sum122.62664
Variance0.2731770013
2020-08-25T01:26:52.769064image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
04813.7%
 
14813.7%
 
-1123.4%
 
-8e-0520.6%
 
-0.0745710.3%
 
0.9652310.3%
 
-0.1383210.3%
 
0.3042110.3%
 
0.3044510.3%
 
-0.0893710.3%
 
0.9204910.3%
 
0.3955910.3%
 
0.4218910.3%
 
-0.9190310.3%
 
0.4059110.3%
 
0.1469410.3%
 
0.7320810.3%
 
0.069910.3%
 
0.5016910.3%
 
0.7083310.3%
 
0.7511510.3%
 
0.6007310.3%
 
0.3338110.3%
 
0.1864110.3%
 
-0.6769910.3%
 
Other values (220)22062.7%
 
ValueCountFrequency (%) 
-1123.4%
 
-0.9190310.3%
 
-0.8138310.3%
 
-0.812110.3%
 
-0.6769910.3%
 
-0.6755310.3%
 
-0.6693210.3%
 
-0.6413410.3%
 
-0.6405610.3%
 
-0.5994310.3%
 
ValueCountFrequency (%) 
14813.7%
 
0.9897110.3%
 
0.9893410.3%
 
0.9881610.3%
 
0.9867410.3%
 
0.984210.3%
 
0.9786110.3%
 
0.9756110.3%
 
0.9724710.3%
 
0.9677810.3%
 

9
Real number (ℝ)

ZEROS

Distinct count267
Unique (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18134538461538463
Minimum-1.0
Maximum1.0
Zeros39
Zeros (%)11.1%
Memory size2.9 KiB
2020-08-25T01:26:52.883420image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.57299
Q1-0.048075
median0.01829
Q30.534195
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.58227

Descriptive statistics

Standard deviation0.4838508883
Coefficient of variation (CV)2.668118019
Kurtosis0.1376096263
Mean0.1813453846
Median Absolute Deviation (MAD)0.14329
Skewness-0.02873843003
Sum63.65223
Variance0.2341116821
2020-08-25T01:26:52.993318image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
03911.1%
 
1288.0%
 
-1174.8%
 
-0.0909120.6%
 
-0.1428620.6%
 
-0.0751420.6%
 
-0.2584310.3%
 
-0.0833710.3%
 
0.3289910.3%
 
-0.4996210.3%
 
0.0106410.3%
 
-0.4044610.3%
 
0.8910910.3%
 
0.5104210.3%
 
-0.0992510.3%
 
0.1296110.3%
 
0.9084210.3%
 
-0.0162210.3%
 
-0.0391110.3%
 
0.3271110.3%
 
0.907410.3%
 
0.5830410.3%
 
0.0117210.3%
 
0.9318210.3%
 
0.9577610.3%
 
Other values (242)24268.9%
 
ValueCountFrequency (%) 
-1174.8%
 
-0.6342710.3%
 
-0.5117110.3%
 
-0.510.3%
 
-0.4996210.3%
 
-0.4310710.3%
 
-0.4044610.3%
 
-0.37510.3%
 
-0.3617410.3%
 
-0.3581810.3%
 
ValueCountFrequency (%) 
1288.0%
 
0.978210.3%
 
0.9653410.3%
 
0.9583310.3%
 
0.9577610.3%
 
0.9519310.3%
 
0.9504110.3%
 
0.9441510.3%
 
0.9359610.3%
 
0.9334510.3%
 

0
Boolean

Distinct count2
Unique (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
1
313
0
 
38
ValueCountFrequency (%) 
131389.2%
 
03810.8%
 

4
Real number (ℝ)

ZEROS

Distinct count204
Unique (%)58.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6010678917378918
Minimum-1.0
Maximum1.0
Zeros38
Zeros (%)10.8%
Memory size2.9 KiB
2020-08-25T01:26:53.111368image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.745815
Q10.41266
median0.8092
Q31
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.58734

Descriptive statistics

Standard deviation0.5198615134
Coefficient of variation (CV)0.864896496
Kurtosis2.129334839
Mean0.6010678917
Median Absolute Deviation (MAD)0.1908
Skewness-1.62777768
Sum210.97483
Variance0.2702559931
2020-08-25T01:26:53.218033image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
19627.4%
 
03810.8%
 
-1164.6%
 
0.967610.3%
 
0.9812210.3%
 
0.3869610.3%
 
0.6666710.3%
 
0.0670410.3%
 
0.8652810.3%
 
0.809210.3%
 
0.656810.3%
 
0.9810310.3%
 
0.6592610.3%
 
0.7231410.3%
 
0.9196610.3%
 
0.9899410.3%
 
0.6733310.3%
 
0.4693910.3%
 
0.8524310.3%
 
0.4666710.3%
 
0.7907810.3%
 
0.5908510.3%
 
0.7306110.3%
 
0.6393510.3%
 
0.9857910.3%
 
Other values (179)17951.0%
 
ValueCountFrequency (%) 
-1164.6%
 
-0.7882410.3%
 
-0.761910.3%
 
-0.7297310.3%
 
-0.5069410.3%
 
-0.3374610.3%
 
-0.3367210.3%
 
-0.3174510.3%
 
-0.2730310.3%
 
-0.0992410.3%
 
ValueCountFrequency (%) 
19627.4%
 
0.9981510.3%
 
0.9979310.3%
 
0.9967210.3%
 
0.9936310.3%
 
0.9935210.3%
 
0.991510.3%
 
0.9899410.3%
 
0.9891910.3%
 
0.9857910.3%
 

16
Real number (ℝ)

ZEROS

Distinct count254
Unique (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.38194900284900285
Minimum-1.0
Maximum1.0
Zeros25
Zeros (%)7.1%
Memory size2.9 KiB
2020-08-25T01:26:53.335605image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.89465
Q10
median0.59091
Q30.935705
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.935705

Descriptive statistics

Standard deviation0.6180203542
Coefficient of variation (CV)1.618070343
Kurtosis-0.5301590085
Mean0.3819490028
Median Absolute Deviation (MAD)0.40909
Skewness-0.8215933853
Sum134.0641
Variance0.3819491582
2020-08-25T01:26:53.441708image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
15916.8%
 
0257.1%
 
-1123.4%
 
-0.37530.9%
 
0.7520.6%
 
0.3658520.6%
 
-0.7543610.3%
 
0.2281310.3%
 
0.4227110.3%
 
0.7827210.3%
 
0.7692910.3%
 
0.5045510.3%
 
-0.789410.3%
 
-0.1311710.3%
 
0.9123610.3%
 
0.6677510.3%
 
0.6702310.3%
 
0.994810.3%
 
0.6614510.3%
 
0.9717310.3%
 
0.9256110.3%
 
0.9326210.3%
 
-0.0376610.3%
 
0.5615610.3%
 
0.6363610.3%
 
Other values (229)22965.2%
 
ValueCountFrequency (%) 
-1123.4%
 
-0.9803910.3%
 
-0.9431510.3%
 
-0.9310410.3%
 
-0.9300110.3%
 
-0.9228210.3%
 
-0.9145610.3%
 
-0.8747410.3%
 
-0.861510.3%
 
-0.8580310.3%
 
ValueCountFrequency (%) 
15916.8%
 
0.996310.3%
 
0.9952810.3%
 
0.994810.3%
 
0.9927310.3%
 
0.9888110.3%
 
0.9887810.3%
 
0.9849710.3%
 
0.9830510.3%
 
0.9786910.3%
 

17
Real number (ℝ)

ZEROS

Distinct count280
Unique (%)79.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0036168091168091113
Minimum-1.0
Maximum1.0
Zeros30
Zeros (%)8.5%
Memory size2.9 KiB
2020-08-25T01:26:53.564438image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.22569
median0
Q30.195285
95-th percentile0.99361
Maximum1
Range2
Interquartile range (IQR)0.420975

Descriptive statistics

Standard deviation0.4967619833
Coefficient of variation (CV)-137.348134
Kurtosis0.008103993261
Mean-0.003616809117
Median Absolute Deviation (MAD)0.21231
Skewness0.005083118602
Sum-1.2695
Variance0.246772468
2020-08-25T01:26:53.674443image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0308.5%
 
-1267.4%
 
1185.1%
 
-0.6862710.3%
 
-0.0319110.3%
 
-0.3969510.3%
 
-0.5777910.3%
 
-0.1190510.3%
 
0.6570110.3%
 
0.6786110.3%
 
0.9872210.3%
 
0.0185210.3%
 
-0.0715710.3%
 
-0.393310.3%
 
0.1956510.3%
 
0.1932810.3%
 
-0.0341610.3%
 
0.0713510.3%
 
-0.0785310.3%
 
0.6238510.3%
 
0.0345810.3%
 
-0.1786310.3%
 
0.8393910.3%
 
0.0194310.3%
 
0.1272210.3%
 
Other values (255)25572.6%
 
ValueCountFrequency (%) 
-1267.4%
 
-0.8329710.3%
 
-0.8300710.3%
 
-0.8155610.3%
 
-0.7960310.3%
 
-0.7777810.3%
 
-0.7720610.3%
 
-0.7195110.3%
 
-0.7172510.3%
 
-0.7072910.3%
 
ValueCountFrequency (%) 
1185.1%
 
0.9872210.3%
 
0.9512210.3%
 
0.9342910.3%
 
0.9162410.3%
 
0.8739610.3%
 
0.8547510.3%
 
0.852110.3%
 
0.8393910.3%
 
0.8281310.3%
 

5
Real number (ℝ)

ZEROS

Distinct count259
Unique (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11588900284900285
Minimum-1.0
Maximum1.0
Zeros46
Zeros (%)13.1%
Memory size2.9 KiB
2020-08-25T01:26:53.795350image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.024795
median0.0228
Q30.334655
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.35945

Descriptive statistics

Standard deviation0.460810129
Coefficient of variation (CV)3.976305928
Kurtosis0.8558761612
Mean0.1158890028
Median Absolute Deviation (MAD)0.14424
Skewness-0.2794400302
Sum40.67704
Variance0.212345975
2020-08-25T01:26:53.908180image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
04613.1%
 
1267.4%
 
-1236.6%
 
-0.0517810.3%
 
0.0459810.3%
 
0.0714310.3%
 
-0.0198910.3%
 
0.2535910.3%
 
-0.1696410.3%
 
-0.0270310.3%
 
-0.0314210.3%
 
-0.0229910.3%
 
0.7765510.3%
 
0.6943810.3%
 
0.0486110.3%
 
0.1625110.3%
 
0.7643210.3%
 
-0.1016910.3%
 
0.0084310.3%
 
0.0741810.3%
 
0.3554310.3%
 
0.3359810.3%
 
-0.6276610.3%
 
-0.1470610.3%
 
0.1828110.3%
 
Other values (234)23466.7%
 
ValueCountFrequency (%) 
-1236.6%
 
-0.8055310.3%
 
-0.7850910.3%
 
-0.7608710.3%
 
-0.7337110.3%
 
-0.6276610.3%
 
-0.4545510.3%
 
-0.3615610.3%
 
-0.3320310.3%
 
-0.296310.3%
 
ValueCountFrequency (%) 
1267.4%
 
0.9076310.3%
 
0.8538810.3%
 
0.8285710.3%
 
0.8216110.3%
 
0.8202110.3%
 
0.8052110.3%
 
0.7857910.3%
 
0.7765510.3%
 
0.7643210.3%
 

13
Real number (ℝ)

ZEROS

Distinct count266
Unique (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09341367521367522
Minimum-1.0
Maximum1.0
Zeros37
Zeros (%)10.5%
Memory size2.9 KiB
2020-08-25T01:26:54.032288image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.073725
median0.03027
Q30.37486
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.448585

Descriptive statistics

Standard deviation0.4948726408
Coefficient of variation (CV)5.297646621
Kurtosis0.2063045796
Mean0.09341367521
Median Absolute Deviation (MAD)0.19107
Skewness-0.2194820172
Sum32.7882
Variance0.2448989306
2020-08-25T01:26:54.141416image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
03710.5%
 
-1246.8%
 
1236.6%
 
-0.1111130.9%
 
0.1176520.6%
 
-0.0143620.6%
 
-0.2727310.3%
 
0.050610.3%
 
-0.4963910.3%
 
0.5884210.3%
 
-0.3767910.3%
 
0.3432810.3%
 
0.951310.3%
 
0.142110.3%
 
-0.3173610.3%
 
0.1515210.3%
 
0.3398710.3%
 
0.0091510.3%
 
0.1041710.3%
 
-0.1424710.3%
 
-0.1258110.3%
 
0.0548910.3%
 
0.8339710.3%
 
-0.089710.3%
 
0.2909110.3%
 
Other values (241)24168.7%
 
ValueCountFrequency (%) 
-1246.8%
 
-0.8937510.3%
 
-0.8640210.3%
 
-0.8572710.3%
 
-0.8484810.3%
 
-0.820910.3%
 
-0.7931310.3%
 
-0.6970710.3%
 
-0.5921210.3%
 
-0.5904310.3%
 
ValueCountFrequency (%) 
1236.6%
 
0.951310.3%
 
0.9394510.3%
 
0.9377810.3%
 
0.8948910.3%
 
0.8933510.3%
 
0.89210.3%
 
0.8824810.3%
 
0.8749310.3%
 
0.8602910.3%
 

11
Real number (ℝ)

ZEROS

Distinct count269
Unique (%)76.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15504045584045587
Minimum-1.0
Maximum1.0
Zeros37
Zeros (%)10.5%
Memory size2.9 KiB
2020-08-25T01:26:54.272383image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.974265
Q1-0.065265
median0.02825
Q30.482375
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.54764

Descriptive statistics

Standard deviation0.4948174492
Coefficient of variation (CV)3.191537631
Kurtosis0.0523178627
Mean0.1550404558
Median Absolute Deviation (MAD)0.20472
Skewness-0.08114890524
Sum54.4192
Variance0.244844308
2020-08-25T01:26:54.381778image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
03710.5%
 
1298.3%
 
-1185.1%
 
-0.1111120.6%
 
0.7374610.3%
 
-0.2571210.3%
 
0.7934610.3%
 
-0.2890910.3%
 
-0.387110.3%
 
0.0141910.3%
 
0.5012210.3%
 
0.832310.3%
 
-0.4244410.3%
 
-0.1107310.3%
 
-0.2407710.3%
 
0.5994210.3%
 
0.3326610.3%
 
-0.0280910.3%
 
0.0257510.3%
 
-0.0749610.3%
 
-0.2164910.3%
 
-0.1173410.3%
 
-0.1775510.3%
 
0.8612110.3%
 
0.0780810.3%
 
Other values (244)24469.5%
 
ValueCountFrequency (%) 
-1185.1%
 
-0.9485310.3%
 
-0.8909810.3%
 
-0.6774310.3%
 
-0.6272310.3%
 
-0.4986310.3%
 
-0.4905710.3%
 
-0.4792910.3%
 
-0.4356910.3%
 
-0.4277810.3%
 
ValueCountFrequency (%) 
1298.3%
 
0.9955710.3%
 
0.9674810.3%
 
0.9630110.3%
 
0.9616710.3%
 
0.9616110.3%
 
0.9612810.3%
 
0.9474910.3%
 
0.9264310.3%
 
0.9245310.3%
 

1
Boolean

CONSTANT
REJECTED

Distinct count1
Unique (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
351
ValueCountFrequency (%) 
0351100.0%
 

2
Real number (ℝ)

ZEROS

Distinct count219
Unique (%)62.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6413418518518519
Minimum-1.0
Maximum1.0
Zeros25
Zeros (%)7.1%
Memory size2.9 KiB
2020-08-25T01:26:54.506012image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.59233
Q10.472135
median0.87111
Q31
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)0.527865

Descriptive statistics

Standard deviation0.4977082025
Coefficient of variation (CV)0.776041983
Kurtosis3.086346703
Mean0.6413418519
Median Absolute Deviation (MAD)0.12889
Skewness-1.851541305
Sum225.11099
Variance0.2477134549
2020-08-25T01:26:54.621006image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
19527.1%
 
0257.1%
 
-1154.3%
 
0.9463110.3%
 
0.9635510.3%
 
0.8501310.3%
 
-0.6793510.3%
 
0.6584510.3%
 
0.3534610.3%
 
0.9243610.3%
 
0.8703210.3%
 
0.8484310.3%
 
0.8885310.3%
 
0.2142910.3%
 
0.894110.3%
 
0.2531610.3%
 
0.9366910.3%
 
0.8757810.3%
 
-0.20510.3%
 
0.8777210.3%
 
0.0385210.3%
 
0.9818210.3%
 
0.4545510.3%
 
0.9800210.3%
 
0.0586610.3%
 
Other values (194)19455.3%
 
ValueCountFrequency (%) 
-1154.3%
 
-0.6793510.3%
 
-0.6562510.3%
 
-0.6428610.3%
 
-0.541810.3%
 
-0.2666710.3%
 
-0.20510.3%
 
-0.0186410.3%
 
-0.0064110.3%
 
0257.1%
 
ValueCountFrequency (%) 
19527.1%
 
0.9970110.3%
 
0.9964510.3%
 
0.9953910.3%
 
0.9944910.3%
 
0.9902510.3%
 
0.9882210.3%
 
0.9845510.3%
 
0.9818210.3%
 
0.9816610.3%
 

target
Boolean

Distinct count2
Unique (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
1
225
0
126
ValueCountFrequency (%) 
122564.1%
 
012635.9%
 

Interactions

2020-08-25T01:26:04.092914image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:04.249366image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:04.402130image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:04.756571image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:04.921834image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:05.092365image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:05.247776image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:05.402018image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:05.557957image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:05.732793image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:05.886390image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:06.041589image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:06.198677image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:06.356292image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:06.516382image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:06.676732image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:06.831850image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:06.983860image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:07.137230image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:07.296528image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:07.449665image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:07.603012image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:07.763270image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:07.922480image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:08.074181image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:08.232528image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:08.396953image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:08.552666image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:08.718147image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:08.899614image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:09.075881image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:09.454187image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:09.614590image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:09.771206image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:09.927907image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:10.084629image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:10.247963image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:10.413640image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:10.583105image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:10.747660image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:10.899652image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:11.051985image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:11.206275image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:11.361424image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:11.514832image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:11.665898image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:11.829999image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:12.003763image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:12.158236image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:12.320782image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:12.472391image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:12.625532image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:12.782559image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:12.935727image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:13.088875image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:13.242263image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:13.403320image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:13.558882image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:13.711416image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:14.072587image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:14.225274image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:14.379464image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:14.537499image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:14.689468image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:14.843367image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:14.995489image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:15.149287image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:15.302634image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:15.453922image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:15.604491image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:15.768173image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:15.929496image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:16.088432image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:16.243310image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:16.403516image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:16.556149image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:16.707933image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:16.861269image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:17.014348image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:17.170456image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:17.325416image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:17.479729image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:17.634079image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:17.792907image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:17.952387image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:18.119375image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:18.281531image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:18.636348image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:18.789168image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:18.956186image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:19.109700image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:19.263812image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:19.418959image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:19.572068image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:19.726446image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:19.876618image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:20.026485image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:20.175014image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:20.322711image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:20.473849image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:20.621990image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:20.775758image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:20.925560image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:21.074953image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:21.220918image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:21.373309image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:21.518464image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:21.667615image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:21.814112image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:21.970088image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:22.117286image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:22.263899image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:22.412756image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:22.568883image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:22.714839image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:23.041771image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:23.189116image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:23.336768image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:23.485935image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:23.631767image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:23.777828image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:23.950300image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:24.094653image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:24.244718image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:24.387456image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:24.534541image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:24.680854image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:24.832786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:24.980465image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:25.141568image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:25.289729image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:25.436806image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:25.584366image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:25.729886image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:25.876577image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:26.026079image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:26.187538image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:26.334492image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:26.483372image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:26.628840image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:26.781820image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:26.929223image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:27.078516image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:27.411135image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:27.560125image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:27.706281image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:27.860568image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:28.011419image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:28.157502image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:28.304772image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:28.461320image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:28.616136image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:28.765368image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:28.916482image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:29.069005image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:29.219408image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:29.363297image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:29.512990image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:29.657172image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:29.804336image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:29.947965image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:30.094568image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:30.241811image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:30.383780image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:30.531038image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:30.678941image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:30.825219image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:30.967743image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:31.115983image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:31.260732image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:31.403518image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:31.730057image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:31.878162image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:32.036058image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:32.189017image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:32.335038image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:32.480906image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:32.632038image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:32.775405image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:32.924243image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:33.071110image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:33.227487image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:33.372052image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:33.517378image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:33.667329image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:33.810695image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:33.964420image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:34.118243image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:34.275762image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:34.420959image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:34.563731image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:34.710669image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:34.854232image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:34.999980image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:35.147074image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:35.290670image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:35.433028image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:35.579194image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:35.723647image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:36.047172image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:36.191746image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:36.337685image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:36.481572image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:36.626385image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:36.770318image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:36.912278image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:37.056382image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:37.212022image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:37.358042image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:37.503109image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:37.651803image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:37.801403image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:37.946476image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:38.090428image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:38.236866image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:38.382335image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:38.527447image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:38.671613image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:38.815273image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:38.970217image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:39.115552image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:39.260658image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:39.422385image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:39.566488image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:39.714773image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:39.863267image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:40.008368image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:40.331059image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:40.482763image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:40.639371image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:40.788639image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:40.941310image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:41.084750image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:41.231966image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:41.376183image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:41.519578image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:41.668284image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:41.818660image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:41.966074image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:42.120025image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:42.267567image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:42.422246image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:42.566566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:42.712353image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:42.866130image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:43.035263image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:43.192003image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:43.340417image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:43.485070image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:43.629340image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:43.779733image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:43.947054image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:44.085529image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:44.231124image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:44.376795image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:44.703566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:44.853040image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:45.003053image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:45.152162image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:45.299435image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:45.445410image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:45.588973image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:45.731536image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:45.877756image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:46.020291image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:46.164742image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:46.311798image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:46.455562image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:46.599271image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:46.740476image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:46.886050image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:47.029963image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:47.180452image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:47.326664image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:47.474451image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:47.631345image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:47.779004image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:47.931373image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:48.079348image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:48.222783image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:48.372777image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:48.525316image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:48.670254image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:49.004793image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:49.149768image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:49.295390image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:49.442857image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:49.585826image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:49.733649image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-08-25T01:26:54.776275image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-08-25T01:26:55.090698image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-08-25T01:26:55.393807image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-08-25T01:26:55.706472image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-08-25T01:26:50.031927image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:26:50.478997image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

1519272682421123290416175131112target
0-0.38223-0.32192-0.461680.410781.000000.56811-0.296740.597550.186410.0376010.852430.84356-0.385420.02306-0.44945-0.1775500.995391
1-0.97515-1.00000-0.18401-0.204681.00000-0.20332-0.453000.34432-0.13738-0.0454910.930350.05499-0.62237-0.36156-0.69707-0.6774301.000000
20.00299-0.08540-0.221450.589840.889650.57528-0.275020.854430.560450.0119811.000000.83775-0.136440.004850.008270.0534601.000001
30.14516-0.544671.000000.516130.000001.000001.000000.00000-0.323820.0000011.000000.54094-0.393301.000000.000000.0000001.000000
4-0.27457-0.17813-0.532060.132900.771520.03286-0.355750.56409-0.04608-0.1639910.941400.52940-0.217800.06531-0.00712-0.2027501.000001
5-0.15540-0.054140.09223-0.032400.147060.035130.036690.00000-0.000390.066371-0.09924-0.00343-0.10196-0.119490.00000-0.0630200.023370
6-0.61436-0.73641-0.825100.136590.859960.22792-0.765620.78225-0.13832-0.2734210.946010.57945-0.68086-0.20800-0.50764-0.4792900.975881
70.00000-1.000001.000001.000000.000001.000000.000000.000000.000000.0000000.000001.000001.000000.000000.00000-1.0000000.000000
8-0.46381-0.66020-0.697120.575771.000000.85106-0.605890.945100.38895-0.3617411.000000.98305-0.35257-0.14333-0.40668-0.4356900.963551
90.386020.22115-0.022940.206450.11470-0.148030.000000.00000-0.08208-0.2681010.00000-0.371330.150180.000000.00000-0.381720-0.018640

Last rows

1519272682421123290416175131112target
3410.023380.052790.072550.967090.947210.941550.055240.978880.972470.0239411.000000.939290.057130.000000.030730.0213000.980021
342-0.073990.06358-0.027310.767170.868210.74451-0.023700.846240.78439-0.0751410.804620.747980.067050.002310.05029-0.1173400.822541
343-0.072890.04992-0.090380.391460.557170.45008-0.087710.620990.28943-0.0611910.693870.42271-0.26409-0.02423-0.06527-0.1046700.353461
3440.008540.038810.013750.708860.799880.771380.011480.830960.638870.0230410.863350.82777-0.069740.002580.007440.1206800.760461
3450.587430.113390.170880.686560.756830.60656-0.449450.401640.13934-0.0027310.974040.767760.318310.06831-0.48907-0.1407100.666671
346-0.089290.066180.001230.834790.904410.953780.011550.811970.90546-0.0462210.737391.00000-0.02101-0.147060.067230.1313000.835081
347-0.013260.060380.049250.935220.945900.945200.084120.941710.914830.0160610.951830.971730.00140-0.027230.073300.0328100.951131
348-0.014610.013930.025420.924890.955840.939880.076770.925950.926970.0244610.932070.948370.02004-0.032270.046880.0176600.947011
349-0.04530-0.12928-0.077600.891470.857460.910500.012150.890610.874030.0011010.981220.91381-0.00884-0.01989-0.01436-0.0331500.906081
350-0.01054-0.03515-0.048220.811470.889280.86467-0.094900.806680.85764-0.0913910.736380.85764-0.04569-0.06151-0.003510.0667800.847101

Duplicate rows

Most frequent

1519272682421123290416175131112targetcount
00.00.0-1.01.00.00.00.00.00.00.000.00.00.00.00.00.000.002